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Zhou, Jiahuan(周嘉欢)
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Assistant Professor, Ph.D. Advisor
Wangxuan Institute of Computer Technology, Peking University.
Beijing, China
E-mail: jiahuanzhou@pku.edu.cn
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About Me
I am now a Tenure-track Assistant Professor (Ph.D. Advisor) in Wangxuan Institute of Computer Technology, Peking University. I received my Ph.D. degree under the supervision of Prof.Ying Wu from Northwestern University in 2018. Before coming to Northwestern, I have received my B.E. degree in the Automation Department from Tsinghua University, Beijing, China in 2013. Before joining Peking University, I was a Postdoctoral Fellow and Research Assistant Professor working with Prof.Ying Wu in Northwestern University.
Opening
We are always actively recruiting Ph.D. students and undergraduate research interns! Welcome to contact me with your detailed CV!
News
Research
Research Interests
Computer Vision
Deep Learning
Data Analysis
Machine Learning
Current Work
Learning from Limited Data (One/Few-shot Learning, Zero-shot Learning, Online learning, Continue learning)
Image and Video Representation Modeling (Retrieval, Identification, Tracking, Recognition)
Machine Learning (Deep Learning, Learning Theory Anlysis, Self-Supervised Learning, Adversarial Leanring)
Multi-Modal Learning
Under Review (*corresponding author)
Jiahuan Zhou, Bing Su*, and Ying Wu "Unsupervised Uncertainty Momentum Modeling for Embedding Learning".
Jiahuan Zhou*, Pengbo Zhao, and Ying Wu, "Full-Reference Image Quality Assessment from Distortion-Guided Hierarchical Attention".
Mingfu Liang, Jiahuan Zhou*, Wei Wei, and Ying Wu, "Balancing between Forgetting and Acquisition in Incremental Subpopulation Learning".
Wei Wei, Jiahuan Zhou*, and Ying Wu, "Improving Adversarial Robustness by Local Structure Preserving".
Recent Publications
Jiahuan Zhou, Bing Su* and Ying Wu, "Discriminative Self-Paced Group-Metric Adaptation for Online Visual Identification", in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI, under Minor revision), 2022.
Bing Su, Jiahuan Zhou*, Jirong Wen, and Ying Wu, "Linear and Deep Order-Preserving Wasserstein Discriminant Analysis", in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2021. [pdf]
Jiahuan Zhou*, Bing Su and Ying Wu, "Online Joint Multi-Metric Adaptation from Frequent Sharing-Subset Mining for Person Re-Identification", in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’20), Seattle, USA, June. 2020. [pdf]
Yansong Tang#, Zanlin Ni#, Jiahuan Zhou, Danyang Zhang, Jiwen Lu, Ying Wu, Jie Zhou., "Uncertainty-aware Score Distribution Learning for Action Quality Assessment", in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’20), Seattle, USA, June. 2020. [pdf]
Bing Su, Jiahuan Zhou, and Ying Wu, "Order-preserving Wasserstein Discriminant Analysis", in Proceedings of IEEE International Conference on Computer Vision (ICCV'19), Seoul, Korea, Oct. 2019. [pdf]
Xu Zou, Sheng Zhong, Luxin Yan, Xiangyun Zhao, Jiahuan Zhou* and Ying Wu, "Learning Robust Facial Landmark Detection via Hierarchical Structured Ensemble", in Proceedings of IEEE International Conference on Computer Vision (ICCV'19), Seoul, Korea, Oct. 2019. [pdf]
Jiahuan Zhou*, and Ying Wu, "Learning Visual Instance Retrieval from Failure: Efficient Online Local Metric Adaptation from Negative Samples", in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2019.[pdf]
Xinzhao Li, Yuehu Liu, Zeqi Chen, Jiahuan Zhou and Ying Wu, "Fused Discriminative Metric Learning for Low Resolution Pedestrian Detection", in Proceedings of IEEE International Conference on Image Processing (ICIP'18), Athens, Greece, Oct. 2018.[pdf]
Jiahuan Zhou*, Bing Su, and Ying Wu, "Easy Identification from Better Constraints: Multi-Shot Person Re-Identification from Reference Constraints", in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'18), Salt Lake City, USA, June. 2018.[pdf]
Jiahuan Zhou*, Pei Yu, Tang Wei, and Ying Wu, "Efficient Online Local Metric Adaptation via Negative Samples for Person Re-Identification", in Proceedings of IEEE International Conference on Computer Vision (ICCV'17), Venice, Italy, Oct. 2017.[pdf]
Wei Tang, Pei Yu, Jiahuan Zhou, and Ying Wu, "Towards a Unified Compositional Model for Visual Pattern Modeling", in Proceedings of International Conference on Computer Vision (ICCV'17), Venice, Italy, Oct. 2017.[pdf]
Bing Su, Jiahuan Zhou, Xiaoqing Ding, and Ying Wu, "Unsupervised Hierarchical Dynamic Parsing and Encoding for Action Recognition", In IEEE Transactions on Image Processing, 26.12 (TIP'2017): 5784-5799.[pdf]
Bing Su, Jiahuan Zhou, Xiaoqing Ding, Hao Wang, and Ying Wu, "Hierarchical Dynamic Parsing and Encoding for Action Recognition", in Proc. European Conf. on Computer Vision (ECCV'16), Amsterdam, Netherlands, Oct. 2016.[pdf]
Pei Yu, Jiahuan Zhou, and Ying Wu, "Learning Reconstruction-based Gaze Estimation", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'16), Las Vegas, USA, June. 2016.[pdf]
Jiahuan Zhou*, and Ying Wu, "Finding the Right Exemplars for Reconstructing Single Image Super-Resolution", in Proc. IEEE Int’l Conf. on Image Processing (ICIP'16, Oral), Phoenix, USA, Sep. 2016.
Han Hu, Jiahuan Zhou, Jianjiang Feng, and Jie Zhou, "Multi-way Constrained Spectral Clustering via Nonnegative Restriction", in Proceeding of International Conference on Pattern Recognition (ICPR'12, Oral), Tsukuba, Japan, Nov. 2012.[pdf]
Note: * indicates the corresponding author; # indicates equal contribution.
Full list of publications in Google Scholar.
Academic Service
Member of the Program Committee (PC):
Area Chair:
IEEE International Conference on Multimedia and Expo (ICME), 2020,2021
26th International Conference on Pattern Recognition, 2022
Conference Reviewer:
European Conf. on Computer Vision (ECCV), 2014, 2018, 2020
IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014-2022
Conference on Neural Information Processing Systems (NeurIPS), 2016
IEEE Int’l Conf. on Computer Vision (ICCV), 2017, 2019, 2021
British Machine Vision Conference (BMVC), 2019
International Conference on Learning Representations (ICLR), 2022
Journal Reviewer:
IEEE Trans on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), 2015-present
IEEE Trans on Circuits and Systems for Video Technology (IEEE TCSVT), 2016-present
IEEE Trans on Image Processing (IEEE TIP), 2017-present
Computer Vision and Image Understanding (CVIU), 2018-present
IEEE Transactions on Information Forensics & Security (IEEE T-IFS), 2019-present
International Journal of Computer Vision (IJCV), 2019-present
Signal, Image and Video Processing (SIVP), 2019-present
Neurocomputing (NEUCOM), 2020-present
Education
Ph.D. in Computer Science, Dept.of EECS, Northwestern University, Evanston, IL, US, Dec.2018
B.E. in Electrical Engineering, Dept.of Automation, Tsinghua University, Beijing, China, Jul.2013
Awards and Honors
Terminal Year Fellowship, Northwestern University, 2018
The Murphy Fellowship, Northwestern University, 2014
Outstanding Graduate Scholarship, Tsinghua University, 2013
Academic Excellence Award, Tsinghua University, 2011
The National Encouragement Scholarship, Tsinghua University, 2010
Experience
Research Intern, Computer Vision Group, Microsoft Research, Redmond, WS, June.2018 - Aug.2018
Research Assistant, Computational Vision Lab, Northwestern University, Evanston, IL, Sep.2013 - Dec.2018
Advisor: Professor Ying Wu
Led several research projects funded by National Science Foundation (NSF), Army Research Office (ARO), Department of Defense (DoD) and so on.
Teaching Assistant, Northwestern University, Evanston, IL, Feb.2014 - June.2017
ELEC-ENG 211, Fundamentals of Computer Programming II
ELEC-ENG 212, Mathematical Foundations of Computer Science
Guest Lecturer, Northwestern University, Evanston, IL, Winter.2019 - Winter.2020
ELEC-ENG 432, Advanced Computer Vision
ELEC-ENG 332, Introduction to Computer Vision
ELEC-ENG 433, Statistical Pattern Recognition
Research Assistant, Laboratory of PRIP in Dept.of Automation, Tsinghua University, Beijing, China, Sep.2012 - June.2013
Advisor: Professor Jianjiang Feng
Proposed a novel algorithm for automatic vehicle detection under both the static and dynamic cameras.
Researched the spectral clustering problem and proposed a novel spectral clustering method.
A brief cv.
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